DBMiner: A System for Mining Knowledge in Large Relational Databases
- Jiawei Han
- Yongjian Fu
- Wei Wang
- Jenny Chiang
- Wan Gong
- Krzysztof Koperski
- Deyi Li
- Yijun Lu
- Amynmohamed Rajan
- Nebozjsa Stefanovic
- Betty B. Xia
- Osmar R. Zaiane, University of Alberta (Database)
A data mining system, DBMiner, has been developed for interactive mining of multiple-level knowledge in large relational databases. The system implements a wide spectrum of data mining functions, including generalization, characterization, association, classi fication, and prediction. By incorporating several interesting data mining techniques, including attribute-oriented induction, statistical analysis, progressive deepening for mining multiple level knowledge, and meta-rule guided mining, the system provides a user-friendly, interactive data mining environment with good performance.
Citation
J. Han, Y. Fu, W. Wang, J. Chiang, W. Gong, K. Koperski, D. Li, Y. Lu, A. Rajan, N. Stefanovic, B. Xia, O. Zaiane. "DBMiner: A System for Mining Knowledge in Large Relational Databases". International Conference on Data Mining and Knowledge Discovery (KDD), Portland, USA, pp 250-255, August 1996.| Keywords: | |
| Category: | In Conference |
| Web Links: | Webdocs |
BibTeX
@incollection{Han+al:KDD96,
author = {Jiawei Han and Yongjian Fu and Wei Wang and Jenny Chiang and Wan
Gong and Krzysztof Koperski and Deyi Li and Yijun Lu and Amynmohamed Rajan
and Nebozjsa Stefanovic and Betty B. Xia and Osmar R. Zaiane},
title = {DBMiner: A System for Mining Knowledge in Large Relational
Databases},
Pages = {250-255},
booktitle = {International Conference on Data Mining and Knowledge Discovery
(KDD)},
year = 1996,
}Last Updated: March 04, 2020Submitted by Sabina P
